
This report observes the potential impact of mentorship on success
factors for LEADS scholars. The outcome Y variables of success factors
will be compared against the X variables ‘priaccess’ or ‘My
primary mentor of mentoring team is accessible’, and
‘prioverall’ or ‘Please rate the overall effectiveness of
your primary mentor.’ The data is unaggregated.
The LEADS survey has been broken down into subscales that will be
assessed in the tabs belows.
Test of Statistical Power for Regression Analysis
##
## Call:
## lm(formula = burnout ~ priaccess, data = plot_data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.7638 -0.5299 -0.2959 0.7041 2.7041
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.46549 0.33582 10.319 < 2e-16 ***
## priaccess -0.23391 0.07601 -3.077 0.00238 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9955 on 198 degrees of freedom
## Multiple R-squared: 0.04565, Adjusted R-squared: 0.04083
## F-statistic: 9.47 on 1 and 198 DF, p-value: 0.002384
Multiple regression power calculation
u = 1
v = 198
f2 = 0.04782827
sig.level = 0.05
power = 0.8681824
Interpretation:
One predictor variable (priaccess). A small effect size, indicating
that while there is a relationship with burnout, it explains only a
small portion of the variance. A high power (87%), suggesting that your
study is well-equipped to detect a significant relationship if it
exists, given your sample size and effect size.
scatterplots
Burnout
Burnout, shown on the y-axis, is measured on a Likert Scale of 1 to 5,
where 1 = None, 2 = Some Stress, 3 = Onset, 4 = Persistence, and 5 =
Severe. In this case, low scores indicate a positive result.

The following plots show the same unaggregated data with a weighted
regression line applied. Weighted regression was chosen to account for
the reflection of n in the plot bubble sizes, aka how many scholars
responded with each combination of scores.

Passion and Interests
Passion and Interest variables on the y-axis are measured on a Likert
Scale of 1 to 5, where 1 = Not at all, 2 = A little, 3 = Neutral, 4 = A
lot, 5 = Very Much.



Leadership
Leadership variables on the y-axis are measured on a Likert Scale of 1
to 7, where 1 = Seldom and 7 = Almost Always.












Research Skills Inventory
Research Skills Inventory variables on the y-axis are measured on a
Likert Scale of 0 to 10. Scholars were asked: Please indicate your
ability to successfully perform each task by selecting a single number
from 0 – 10 that best describes your level of confidence. We would like
to know how confident you are that you can successfully perform these
tasks TODAY where 0 = No confidence, 10 = Total confidence.



















Professionalism
Professionalism variables on the y-axis are measured on a Likert Scale
of 1 to 5, where 1 = Never and 5 = A great deal.







Research Experience
Research experience, seen on the y-axis, is measured on a Likert Scale
of 0 to 5, where 0 = Has not changed at all, and 5 = Has changed a great
deal.

Networking/Social Capital
Networking and social capital variables on the y-axis are measured on a
Likert Scale of 0 to 10, where 0 = Not at all, 10 = Completely.






Job Satisfaction
Job satisfaction variables on the y-axis are measured on a Likert Scale
of 1 to 7, where 1 = Strongly disagree and 7 = Strongly agree.







Career Satisfaction
Career satisfaction variables on the y-axis are measured on a Likert
Scale of 1 to 5, where 1 = Not satisfied, 5 = Very satisfied.


Career Adapt-Abilities Inventory
Career Adat-Abilities Inventory variables on the y-axis are measured on
a Likert Scale of 1 to 5. Scholars were provided with the following
promt: Different people use different strength to build their careers.
No one is good at everything, each of us emphasizes some strengths more
than others. Please rate how strongly you have developed each of the
following abilities using the scale below where 1 = Not strong and 5 =
Strongest.























